"iekām", "iekāms", "kolīdz", "līdzko", "tiklīdz", "jebšu", "tālab", "tāpēc", "nekā", "itin", "jā", "jau", "jel", "nē", "nezin", "tad", "tikai", "vis", "tak", "iekams", "vien", "# modal verbs", "būt  ", "biju ", "biji", "bija", "bijām", "bijāt", "esmu", "esi", "esam", "esat ", "būšu     ", "būsi", "būs", "būsim", "būsiet", "tikt", "tiku", "tiki", "tika", "tikām", "tikāt", "tieku", "tiec", "tiek", "tiekam", "tiekat", "tikšu", "tiks", "tiksim", "tiksiet", "tapt", "tapi", "tapāt", "topat", "tapšu", "tapsi",...

"iekām", "iekāms", "kolīdz", "līdzko", "tiklīdz", "jebšu", "tālab", "tāpēc", "nekā", "itin", "jā", "jau", "jel", "nē", "nezin", "tad", "tikai", "vis", "tak", "iekams", "vien", "# modal verbs", "būt  ", "biju ", "biji", "bija", "bijām", "bijāt", "esmu", "esi", "esam", "esat ", "būšu     ", "būsi", "būs", "būsim", "būsiet", "tikt", "tiku", "tiki", "tika", "tikām", "tikāt", "tieku", "tiec", "tiek", "tiekam", "tiekat", "tikšu", "tiks", "tiksim", "tiksiet", "tapt", "tapi", "tapāt", "topat", "tapšu", "tapsi",...

  public static Predicate<CharSequence> contains(Pattern pattern) {
    return new ContainsPatternPredicate(new JdkPattern(pattern));
  }

  // End public API, begin private implementation classes.

  private enum ObjectPredicate implements Predicate<@Nullable Object> {
    /**
     * @see Predicates#alwaysTrue()
     */
    ALWAYS_TRUE {
      @Override
      public boolean apply(@Nullable Object o) {

            if (tempStr != null) {
                tempStr.intern();
            }
        }
    }

    /**
     * Authentication strategy
     *
     *
     */
    public enum AuthenticationType {
        /**
         * Null/anonymous authentication
         *
         * Login with no credentials
         */
        NULL,
        /**
         * Guest authentication

        Keras training loops like `fit`/`evaluate`, the unreduced vector loss is
        passed to the optimizer but the reported loss will be a scalar value.
    *   `SUM`: Scalar sum of weighted losses. 4. `SUM_OVER_BATCH_SIZE`: Scalar
        `SUM` divided by number of elements in losses. This reduction type is
        not supported when used with `tf.distribute.Strategy` outside of
        built-in training loops like `tf.keras` `compile`/`fit`.

  public void testToImmutableSortedMapMerging() {
    Collector<Entry<String, Integer>, ?, ImmutableSortedMap<String, Integer>> collector =
        toImmutableSortedMap(naturalOrder(), Entry::getKey, Entry::getValue, Integer::sum);
    Equivalence<ImmutableMap<String, Integer>> equivalence =
        Equivalence.equals().<Entry<String, Integer>>pairwise().onResultOf(ImmutableMap::entrySet);
    CollectorTester.of(collector, equivalence)

      if (newArg == null || Objects.equals(args.get(i), newArg)) {
        if (params.get(i).getType().getRawType().isEnum()) {
          continue; // Nothing better we can do if it's single-value enum
        }
        throw new ParameterHasNoDistinctValueException(params.get(i));
      }
      newArgs.set(i, newArg);
      tester.addEqualityGroup(createInstance(factory, newArgs));

   * char[])}.
   *
   * @since 2.0
   */
  public static Comparator<char[]> lexicographicalComparator() {
    return LexicographicalComparator.INSTANCE;
  }

  private enum LexicographicalComparator implements Comparator<char[]> {
    INSTANCE;

    @Override
    public int compare(char[] left, char[] right) {
      int minLength = Math.min(left.length, right.length);

   * float[])}.
   *
   * @since 2.0
   */
  public static Comparator<float[]> lexicographicalComparator() {
    return LexicographicalComparator.INSTANCE;
  }

  private enum LexicographicalComparator implements Comparator<float[]> {
    INSTANCE;

    @Override
    public int compare(float[] left, float[] right) {
      int minLength = Math.min(left.length, right.length);

   * order.
   */
  @Override
  // TODO(kevinb): caveats about equivalence-relation?
  boolean equals(@Nullable Object object);

  /**
   * Returns the hash code for this multiset. This is defined as the sum of
   *
   * {@snippet :
   * ((element == null) ? 0 : element.hashCode()) ^ count(element)
   * }
   *
   * <p>over all distinct elements in the multiset. It follows that a multiset and its entry set